Development of classification models for identifying "true" P-glycoprotein (P-gp) inhibitors through inhibition, ATPase activation and monolayer efflux assays

Simona Rapposelli, Alessio Coi, Marcello Imbriani, Anna Maria Bianucci

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

P-glycoprotein (P-gp) is an efflux pump involved in the protection of tissues of several organs by influencing xenobiotic disposition. P-gp plays a key role in multidrug resistance and in the progression of many neurodegenerative diseases. The development of new and more effective therapeutics targeting P-gp thus represents an intriguing challenge in drug discovery. P-gp inhibition may be considered as a valid approach to improve drug bioavailability as well as to overcome drug resistance to many kinds of tumours characterized by the over-expression of this protein. This study aims to develop classification models from a unique dataset of 59 compounds for which there were homogeneous experimental data on P-gp inhibition, ATPase activation and monolayer efflux. For each experiment, the dataset was split into a training and a test set comprising 39 and 20 molecules, respectively. Rational splitting was accomplished using a sphere-exclusion type algorithm. After a two-step (internal/external) validation, the best-performing classification models were used in a consensus predicting task for the identification of compounds named as "true" P-gp inhibitors, i.e., molecules able to inhibit P-gp without being effluxed by P-gp itself and simultaneously unable to activate the ATPase function.

Original languageEnglish
Pages (from-to)6924-6943
Number of pages20
JournalInternational Journal of Molecular Sciences
Volume13
Issue number6
DOIs
Publication statusPublished - Jun 2012

Fingerprint

efflux
Glycoproteins
P-Glycoprotein
inhibitors
Adenosine Triphosphatases
Monolayers
Assays
drugs
Chemical activation
activation
bioavailability
exclusion
progressions
organs
molecules
education
tumors
pumps
proteins
Neurodegenerative diseases

Keywords

  • Classification model
  • Consensus model
  • Decision trees
  • MDR1 ligands
  • P-glicoprotein
  • P-gp inhibitors

ASJC Scopus subject areas

  • Computer Science Applications
  • Molecular Biology
  • Catalysis
  • Inorganic Chemistry
  • Spectroscopy
  • Organic Chemistry
  • Physical and Theoretical Chemistry
  • Medicine(all)

Cite this

Development of classification models for identifying "true" P-glycoprotein (P-gp) inhibitors through inhibition, ATPase activation and monolayer efflux assays. / Rapposelli, Simona; Coi, Alessio; Imbriani, Marcello; Bianucci, Anna Maria.

In: International Journal of Molecular Sciences, Vol. 13, No. 6, 06.2012, p. 6924-6943.

Research output: Contribution to journalArticle

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